• Title/Summary/Keyword: factory automation

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Present Situation and Propulsion Strategy of Factory Automation in Manufacturing Company (제조기업의 공장자동화 현황과 추진전략에 관한 연구)

  • 이덕수;박노국;송문익
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.18 no.36
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    • pp.233-241
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    • 1995
  • Many companies worldwide today are pursuing to make diversified and highly qualified products. Factory automation aims at maximizing profits through the lessened inventory and shortened delivery time, which will enable the company to become more responsive to market changes. This research analyzes the following feartures in the process of factory automation. first, the automation level according to the company class. second, productivity according to the automation level. third, the organization menber's interest in the automation. finally, the possible problems in factory automation.

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An automaticity indicator computation and a factory automation procedure (자동화 지표 계산 및 공장자동화 순서 결정을 위한 방법)

  • Cho, Hyun-Bo;Jeong, Ki-Yong;Lee, In-Bom;Joo, Jae-Koo;Lee, Joo-Kang;Jeon, Jong-Hag
    • IE interfaces
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    • v.10 no.1
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    • pp.209-222
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    • 1997
  • The paper provides a methodology to obtain the automaticity indicator of a factory and the sequence of enabling technologies of factory automation. The automaticity indicator is the measure of the current automation status of a factory and can be used as a crucial criteria for the future automation schedule and investment. Although most industries have their own computation methods which usually consider the number of workers in the shop floor, this research covers five evaluation items of automation, such as, production facility, material transfer system, inspection and test system, information system, and flexibility. The detailed evaluation models are developed for each item. Automation sequencing prioritizes the enabling technologies of factory automation on the basis of several criteria which consist of two phases. The first phase includes the automation indicator and the second phase includes six sub-criteria such as production rate, quality, number of workers, capital investment, development duration, development difficulty. For this evaluation, AHP(Analytical Hierarchy Process) is introduced to prevent the decision maker's subject intention. As results of the automaticity indicator and automation sequence, the manager can save time and cost in building constructive and transparent automation plans.

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Design and Implementation of Quality Evaluation Tool for factory Automation Software (공장자동화용 소프트웨어에 대한 품질평가 도구의 설계 및 구현)

  • 양해술;이하용;황석형
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.1 no.1
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    • pp.55-62
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    • 2000
  • Factory automation of enterprise has become one of the most important method that acquire competition power. Therefore, it is necessary to evaluate quality of automation software for quality enhancement of factory automation system. duality is affected to technical quality of software in automation of making. In this study, we established a quality evaluation system, evaluation Process and metrics for factory automation software, and implemented quality evaluation tool which can support quality progress of automated software.

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The Effect of Both Employees' Attitude toward Technology Acceptance and Ease of Technology Use on Smart Factory Technology Introduction level and Manufacturing Performance (종업원 기술수용태도와 기술 사용용이성이 스마트공장 기술 도입수준과 제조성과에 미치는 영향)

  • Oh, Ju Hwan;Seo, Jin Hee;Kim, Ji Dae
    • Journal of Information Technology Applications and Management
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    • v.26 no.2
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    • pp.13-26
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    • 2019
  • The purpose of this study is to examine the effect of each of the two technology acceptance factors(employees' attitude toward smart factory technology, and ease of smart factory technology use) on the introduction level of each of the three smart factory technologies (manufacturing big data technology, automation technology, and supply chain integration technology), and in turn, the effect of each of the three smart factory technologies on manufacturing performance. This study employed PLS statistics software package to empirically validate a structural equation model with survey data from 100 domestic small-and medium-sized manufacturing firms (SMMFs). The analysis results revealed the followings. First, it is founded that employees' attitude toward smart factory technology influenced all of the three smart factory technology introduction levels in a positive manner. In particular, SMMFs of which employees had more favorable attitude toward smart factory technology tended to increase introduction levels of both automation technology and supply chain integration technology more than in the case of manufacturing big data technology. Second, ease of smart factory technology use also had a positive impact on each of the three smart factory technology introduction levels, respectively. A noteworthy finding is this : SMMFs which perceived smart factory technology as easier to use would like to elevate the introduction level of manufacturing big data technology more than in the cases of either automation technology or supply chain integration technology. Third, smart factory technologies such as automation technology and supply chain integration technology had affirmative impacts on manufacturing performance of SMMFs. These results shed some valuable insights on the introduction of smart factory technology : The success of smart factory heavily depends on organization-and people-related factors such as employees' attitude toward smart factory technology and employees' perceived ease of smart factory technology use.

Trends of communication network technologies for factory automation (공장 자동화용 네트워크의 기술 동향)

  • Choi, Yobb
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10b
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    • pp.376-381
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    • 1987
  • There are many kinds of intelligent devices on the factory floor nowadays. Standardized communication methods became a necessity for efficient flow of production information among various systems. MAP (Manufacturing Automation Protocol) based on ISO (International Standard Organization) OSI (Open Systems Interconnection) is gaining acceptance of major industries worldwide.

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Plan for Risk Reduction of Smart Factory Process through Accident Analysis and Status Survey (재해분석과 실태조사를 통한 스마트 팩토리 공정의 위험성 감소 방안)

  • Byeon, Junghwan
    • Journal of the Korean Society of Safety
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    • v.37 no.5
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    • pp.22-32
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    • 2022
  • The domestic smart factory is being built and spread rapidly, mainly by mid-sized companies and large enterprises according to the government's active introduction and support policy. But these factories only promote production system and efficiency, so harmfulness and risk factors are not considered. Therefore, to derive harmful risk factors in terms of industrial safety for 12,983 government-supported smart factory workplaces from 2014 to 2019, industrial accident status analysis compared workplaces with automation facilities and government-supported workplaces with automation facilities. Also, to reduce risks associated with domestic smart factory processes, twenty government-supported workplaces with automation facilities underwent analysis, evaluating risks through a status survey using the process evaluation table. In addition, the status survey considered region, size, industry, construction level, and accident rate; the difference in risk according to the structure of the process was confirmed. Based on the smart factory process evaluation results, statistical analysis confirmed that serial, parallel, and hybrid structures pose different risk levels and that the risks of mixed structures are greater. Finally, safety control system application was presented for risk assessment and reduction in the smart factory process, reflecting the results of disaster analysis and actual condition investigation.

A System Architecture for Facility Fault Diagnosis and Repair Action in Smart Factory (스마트 팩토리에서 설비 장애 진단 및 조치 시스템 구조)

  • Cho, Jaehyung;Lee, Jaeoh
    • KNOM Review
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    • v.23 no.1
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    • pp.18-25
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    • 2020
  • Recently, a research on a smart factory was developed from a concept of factory automation(FA) to the formation of collecting and analyzing data. This trend is accelerated as the development of communication technology(5G) and IoT devices are developed in various ways according to the field situation. In addition, digital transformation has been actively conducted in the strengthening corporate competitiveness, and various optimization studies are being conducted through process re-adjustment by combining data received from various IoT equipment and automated facilities. Therefore, in this paper, we propose a system architecture and its related components in diagnosing and repairing facility failure using a prediction system which is one of the related researches.